Wilks¶
- class Wilks(*args)¶
Class to evaluate the Wilks number.
Refer to Estimation of a quantile by Wilks’ method.
- Parameters:
- randomVector
RandomVector
of dimension 1 Output variable of interest.
- randomVector
Notes
This class is a static class which enables the evaluation of the Wilks number: the minimal sample size to perform in order to guarantee that the empirical quantile , noted evaluated with the maximum of the sample, noted be greater than the theoretical quantile with a probability at least :
where .
Methods
ComputeSampleSize
(quantileLevel, confidenceLevel)Evaluate the size of the sample.
computeQuantileBound
(quantileLevel, ...[, ...])Evaluate the bound of the quantile.
- __init__(*args)¶
- static ComputeSampleSize(quantileLevel, confidenceLevel, marginIndex=0)¶
Evaluate the size of the sample.
- Parameters:
- alphapositive float
The order of the quantile we want to evaluate.
- betapositive float
Confidence on the evaluation of the empirical quantile.
- iint
Rank of the maximum which will evaluate the empirical quantile. Default (maximum of the sample)
- Returns:
- wint
the Wilks number.
- computeQuantileBound(quantileLevel, confidenceLevel, marginIndex=0)¶
Evaluate the bound of the quantile.
- Parameters:
- alphapositive float
The order of the quantile we want to evaluate.
- betapositive float
Confidence on the evaluation of the empirical quantile.
- iint
Rank of the maximum which will evaluate the empirical quantile. Default (maximum of the sample)
- Returns:
- q
Point
The estimate of the quantile upper bound for the given quantile level, at the given confidence level and using the given upper statistics.
- q
Examples using the class¶
Estimate Wilks and empirical quantile